function [probability] =  clusterProbabilty(trainData, testData)

    center = mean(trainData, 2);
    clustSTD = std(trainData,0,2);
    
    diff = abs(center - testData);
    
    %This trains the cluster to get 100% probablity that the trained is
    %correct
    a = ones(1, size(trainData,2));
    test = center * a;
    b = abs(trainData - test);
    repeatSTD = clustSTD * a;
    numSTD = b ./ repeatSTD;
    numSTD = max(max(numSTD));
    
    pass = (numSTD * clustSTD) >= diff;
    
    probability = sum(pass)/size(pass,1);


end

